scholarly journals CHARGE RADII OF HYPERONS

1995 ◽  
Vol 10 (28) ◽  
pp. 2103-2111 ◽  
Author(s):  
SARIRA SAHU

The momentum projected SU(3) chiral color dielectric model (CCDM) is employed to calculate the charge root mean square radii and charge distribution of hyperons. The gluonic and pionic contributions are treated perturbatively. We compare our result with that of Skyrme, MIT bag and cloudy bag model. The charge distribution of Λ in CCDM is similar to that of Skyrme model prediction.

1987 ◽  
Vol 13 (10) ◽  
pp. 1261-1267 ◽  
Author(s):  
J I Escudero ◽  
F Barranco ◽  
G Madurga

1982 ◽  
Vol 15 (2) ◽  
pp. 149-153 ◽  
Author(s):  
Stanislav Dubnička ◽  
Anna Zuzana Dubničková ◽  
Štefan Dubnička

2014 ◽  
Vol 29 (39) ◽  
pp. 1450208 ◽  
Author(s):  
Ozan Artun ◽  
Çağlar Aytekin ◽  
Hüseyin Aytekin

In this study, we have calculated the basic nuclear properties such as binding energies, root mean square (rms) charge radii, and neutron and proton densities of the even–even natural 92–100 Mo isotopes. Investigations were performed using the Hartree–Fock–Bogoliubov (HFB) method with different Skyrme-like forces. Separation energies, which have an important role in nuclear structure, of neutron, proton, deuteron, triton, helium-3 and alpha were also investigated with TALYS 1.4 code. The calculated results were discussed and compared with experimental results.


1969 ◽  
Vol 24 (5) ◽  
pp. 858-859 ◽  
Author(s):  
Hans Alfred Bentz

Abstract From elastic electron scattering between 30 and 60 MeV, the following essentially model independent rms charge radii (fm) have been deduced: 2.395 + 0.028 (12C) ; 2.492 + 0.033 (14N) ;2.666± 0.033 (16O). An improved value for 9Be is (2.43 ±0.08) fm.


2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  

2021 ◽  
Vol 13 (9) ◽  
pp. 1630
Author(s):  
Yaohui Zhu ◽  
Guijun Yang ◽  
Hao Yang ◽  
Fa Zhao ◽  
Shaoyu Han ◽  
...  

With the increase in the frequency of extreme weather events in recent years, apple growing areas in the Loess Plateau frequently encounter frost during flowering. Accurately assessing the frost loss in orchards during the flowering period is of great significance for optimizing disaster prevention measures, market apple price regulation, agricultural insurance, and government subsidy programs. The previous research on orchard frost disasters is mainly focused on early risk warning. Therefore, to effectively quantify orchard frost loss, this paper proposes a frost loss assessment model constructed using meteorological and remote sensing information and applies this model to the regional-scale assessment of orchard fruit loss after frost. As an example, this article examines a frost event that occurred during the apple flowering period in Luochuan County, Northwestern China, on 17 April 2020. A multivariable linear regression (MLR) model was constructed based on the orchard planting years, the number of flowering days, and the chill accumulation before frost, as well as the minimum temperature and daily temperature difference on the day of frost. Then, the model simulation accuracy was verified using the leave-one-out cross-validation (LOOCV) method, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized root mean square error (NRMSE) were 0.69, 18.76%, and 18.76%, respectively. Additionally, the extended Fourier amplitude sensitivity test (EFAST) method was used for the sensitivity analysis of the model parameters. The results show that the simulated apple orchard fruit number reduction ratio is highly sensitive to the minimum temperature on the day of frost, and the chill accumulation and planting years before the frost, with sensitivity values of ≥0.74, ≥0.25, and ≥0.15, respectively. This research can not only assist governments in optimizing traditional orchard frost prevention measures and market price regulation but can also provide a reference for agricultural insurance companies to formulate plans for compensation after frost.


Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.


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